Lies, Damned Lies, and Statistics

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Author: Uri Dadush
Originally published by Foreign Policy

During the presidential campaign that just concluded, not a day went by without Mitt Romney trotting out the Chinese bogeyman, a looming red specter racking up a tremendous trade surplus and sapping Americans of their confidence. “It’s pretty clear who doesn’t want a trade war. And there’s one going on right now, which we don’t know about. It’s a silent one. And they’re winning,” Romney declared during the third and final debate. The point was a politically useful one for the Republican challenger, but did he really know how big the trade deficit with China is and what it implies?

Such statistics play an extraordinarily important role in the analysis and formulation of government policy. But even when they are not used as political fodder, they are often misleading, and once they become the established way of measuring things, special interests latch on to them and make it almost impossible to change the metrics used. Greater discrimination should be used with statistics, and voters should insist that political leaders use and invest in statistics that accurately reflect what they are intended to measure.

Take exports, which have traditionally been reported on a gross basis — simply the dollar value of what is exported. Such data is of limited economic consequence because nowadays, recorded exports very often consist of large amounts of imported inputs, ranging from petroleum to sophisticated machine tools, as distinct from value added domestically, such as the design and assembly of a jet fighter or an earth-moving machine.

Responding to this criticism, the Organization for Economic Cooperation and Development and World Trade Organization have just released a new dataset based on the domestic value added of exports that transforms the way trade is viewed. They show that China’s bilateral trade surplus with the United States is about 25 percent smaller than previously reported because so much of China’s exports consist of the assembly of parts produced elsewhere, including in the United States. Moreover, the statistics illustrate more clearly than ever before how interconnected economies around the world have become, and how attempts to restrict imports — such as those Romney was effectively advocating — are likely to backfire not only because other countries will retaliate but also because domestic production will quickly become uncompetitive or even grind to a halt due to lack of parts or raw materials.

The new data also indicates that, contrary to general belief, the United States’ service exports are about as large as its manufactured exports. Because domestically produced services such as transport and financial and legal services are exported both directly and indirectly as part of the domestic value-added of manufactured exports, traditional ways of measuring exports underestimate the importance of services as generators of foreign exchange. For example, much of what is reported as export of a Boeing aircraft actually includes a large proportion of services Boeing has purchased from U.S. service providers — everything from janitors to lawyers to local government officials.

But while these statistics shed new light on how to measure economic output, do not expect textile or steel producers to adopt them any time soon. Given their interest in playing up the importance of manufacturing, these groups have a vested interest in maintaining the outdated economic statistics. The same applies to China-bashers interested in playing up the size of the bilateral trade deficit.

And trade is just one of many instances where standard economic statistics present a misleading picture of reality. Take the government budget deficit — the difference between the government’s total expenditures in a given year and its revenues from taxes, fees, and other miscellaneous revenue sources. This method of calculating the budget deficit is useful to understand how much the government needs to borrow each year, but the deficit fails to capture far more important dynamics in government spending and future obligations.

As Boston University economist Laurence Kotlikoff has long argued, in his article Deficit Delusion and elsewhere, the economic significance of the budget deficit as traditionally measured is, well, minuscule. What really matters for assessing the solvency of the government is not current cash outlays and receipts, but its overall balance sheet and how it is changing, notably through the new commitments it undertakes each year and the tax revenue it can expect in coming decades. It is therefore possible for the government to show a cash surplus in a given year but for its net liabilities to rise because life expectancy has risen or a new pension or health care scheme has been introduced that will draw on resources for many years to come.

As populations have aged and health-care costs have steeply increased in advanced countries, the cash deficit has tended to greatly underestimate the true deficit. Long-term budget projection models have been developed that incorporate demographic, productivity, and other trends to evaluate the true budget situation of countries. Although the results are widely available, they remain, by and large, invisible to the public eye, the province of policy wonks.

Instead, simple economic questions such as the size of the economic pie are obscured behind economic statistics that fail to accurately reflect the underlying economic reality. Gross domestic product, for instance — the sum total of all things produced in an economy — provides a very partial and vastly distorted picture of a nation’s well-being. The measure fails to account for factors such as the cost of environmental pollution, urban congestion, and the depletion of natural resources that is associated with the economic activity it measures.

The growth of GDP per capita, the most widely used measure of economic progress, can also produce a vastly misleading picture because it fails to account for income distribution. From 1979 to 2007, for example, the United States saw average GDP per capita rise by 62 percent in real terms, but its median GDP per capita, the income level that half of families exceed, grew by just 35 percent. This is because the gains of economic growth have accrued overwhelmingly to the top of the income spectrum, a fact that remained obscured during the recent boom years and has only recently gained political attention.

For ordinary people, inflation remains far and away the most important economic statistic — many a revolution, after all, has found its spark in rising bread prices. Still, despite numerous attempts to rework it in the United States, Britain, and elsewhere, the standard measure of inflation, the consumer price index, tends to overstate inflation because it does not adequately account for quality improvements. The car I own today, for example, is a much safer, more comfortable, and more fuel-efficient vehicle than the one I bought when I was in graduate school almost 40 years ago. But the consumer price index would have me believe that it is far more expensive while not accounting for the fact that I have gotten much more for my buck.

The consumer price index can also overstate inflation because it does not adequately account for the fact that consumers buy fewer products and services whose prices rise faster. A “chain-weighted” index has been developed that updates the weights of different products every year to reflect the most recent choices of consumers and results in lower and more accurate inflation estimates, but its use to compute the inflation adjustment of social security benefits is fiercely resisted by advocacy groups like the American Association of Retired People, as a lower figure for inflation would result in lower cost-of-living adjustments for retired seniors.

Why do such statistics continue to be used when many now recognize that they are deeply flawed? Sheer inertia is part of the explanation, and gathering more nuanced and better-targeted statistics and disseminating them is costly. But perhaps the most important reason is that powerful interest groups latch on to the commonly used statistics that suit them.

Particular groups should have the right to their own view, but not to their own facts. Political leaders in the United States and around the world should invest in statistics that tell the truth and treat headline figures with healthy skepticism. Those charged with the big decisions that determine lives should be expected to delve deeper into what is really going on.

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